{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "pursuant-chambers",
   "metadata": {
    "nbsphinx": "hidden"
   },
   "outputs": [],
   "source": [
    "# This is a hidden cell which will be executed but will not show up in Sphinx docs.\n",
    "# To hide a cell, in Jupyter go to Menu->View->Cell Toolbar->Edit Metadata\n",
    "# and enter in {\"nbsphinx\": \"hidden\"}\n",
    "\n",
    "# Set figure size and font size\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['figure.figsize'] = [8, 4]\n",
    "plt.rcParams['font.size'] = 12\n",
    "\n",
    "# Configure quickplot to hide subports\n",
    "import functools\n",
    "from phidl import quickplot as qp, set_quickplot_options\n",
    "import phidl\n",
    "set_quickplot_options(show_subports = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "international-jacksonville",
   "metadata": {},
   "source": [
    "# Layers\n",
    "\n",
    "Layers are an important component of GDSII design.  Layers in a GDS file are defined using two integers (0-255): a `layer` and a `datatype`.  In PHIDL, the layer can be specified...\n",
    "\n",
    " 1. as a single number `0`-`255` representing the gds layer number (gds datatype will be set to `0`)\n",
    " 2. as a 2-element list `[0,1]` or tuple `(0,1)` representing the (layer, datatype)\n",
    " 3. as a Layer / LayerSet object\n",
    "\n",
    "To begin, let's make a new blank device `D` and add some text-polygons to it using different methods of layer entry:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "boring-arrest",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import phidl.geometry as pg\n",
    "from phidl import Device, Layer, LayerSet\n",
    "from phidl import quickplot as qp\n",
    "\n",
    "\n",
    "D = Device()\n",
    "\n",
    "# Specify layer with a single integer 0-255 (gds datatype will be set to 0)\n",
    "layer1 = 1\n",
    "\n",
    "# Specify layer as 1, equivalent to layer = 2, datatype = 6\n",
    "layer2 = (2,6)\n",
    "\n",
    "# Specify layer as 2, equivalent to layer = 2, datatype = 0\n",
    "layer3 = Layer(gds_layer = 3, gds_datatype = 5, color = 'gold')\n",
    "\n",
    "D << pg.text('Layer (1,0)', layer = layer1)\n",
    "D << pg.text('Layer (2,6)', layer = layer2).movey(-20)\n",
    "D << pg.text('Layer (3,5)', layer = layer3).movey(-40)\n",
    "\n",
    "qp(D)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "martial-appreciation",
   "metadata": {},
   "source": [
    "## Multiple layers\n",
    "\n",
    "Say we want to create the same ellipse on several different layers.  We can do that by using a Python `set` of layers, which is created using the curly brackets `{}` (similar to a dict but without colons).  So if we want to add it to four layers, say:\n",
    "- layer 1 / datatype 0\n",
    "- layer 3 / datatype 5\n",
    "- layer 3 / datatype 6\n",
    "- layer 7 / datatype 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "caroline-ultimate",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Note each element of the set must be a valid layer input by itself\n",
    "my_layers = {1, (3,5), (3,6), (7,8)}\n",
    "D = pg.ellipse(layer = my_layers)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "established-yorkshire",
   "metadata": {},
   "source": [
    "Note that although we specified four different layers, it did **not** produce four separate ellipse Devices--instead, it produced one Device with all four ellipse polygons inside that single Device."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "scientific-nursing",
   "metadata": {},
   "source": [
    "### LayerSet\n",
    "\n",
    "PHIDL also has a convenience container for layers called a `LayerSet`, which lets you conveniently call each Layer object just by its name.  You can also specify the layer color using an RGB triplet e.g `(0.1, 0.4, 0.2)`, an HTML hex color (e.g. `#a31df4`), or a CSS3 color name (e.g. `'gold'` or `'lightblue'` see http://www.w3schools.com/colors/colors_names.asp ) The `'alpha'` argument also lets you specify how transparent that layer should look when using `quickplot()` (has no effect on the written GDS file).\n",
    "\n",
    "We construct a layerset by starting with a blank one, and then using the `add_layer()` function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "running-practitioner",
   "metadata": {},
   "outputs": [],
   "source": [
    "ls = LayerSet() # Create a blank LayerSet\n",
    "\n",
    "ls.add_layer(name = 'au', gds_layer = 4, gds_datatype = 0, \n",
    "             description = 'Gold wiring', color = 'goldenrod')\n",
    "ls.add_layer(name = 'nb', gds_layer = 5, gds_datatype = 0, \n",
    "             description = 'Niobium liftoff', color = (0.4,0.5,0.7))\n",
    "ls.add_layer('nb_etch', 6, 0, color = 'lightblue', alpha = 0.2)\n",
    "ls.add_layer('silicon', 8, 2, color = 'green', alpha = 0.4)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dutch-voltage",
   "metadata": {},
   "source": [
    "Now that our layers are defined, we can call them from the LayerSet in the same way we would from a dictionary, where the name becomes the key:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "decreased-arlington",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "D = Device()\n",
    "\n",
    "gold_layer = ls['au']\n",
    "\n",
    "D.add_ref( pg.text('Gold layer', size = 10, layer = ls['au']) ).movey(0)\n",
    "D.add_ref( pg.text('Niobium layer', size = 10, layer = ls['nb']) ).movey(-20)\n",
    "D.add_ref( pg.text('Nb Etch layer', size = 10, layer = ls['nb_etch']) ).movey(-40)\n",
    "D.add_ref( pg.text('Si layer', size = 10, layer = ls['silicon']) ).movey(-60)\n",
    "\n",
    "qp(D)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "prerequisite-hampton",
   "metadata": {},
   "source": [
    "We can additionally use a LayerSet to add the same structure to several layers at once by passing the whole layerset to the layer argument.  Note that since they all overlap, it will look like a single object (but rest assured there are multiple layers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "listed-disclaimer",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "T = pg.text('All layers', layer = ls)\n",
    "qp(T)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "alert-migration",
   "metadata": {},
   "source": [
    "If we want to examine any single layer, we can call them by their names,\n",
    "for example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "domestic-decision",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Layer (name nb, GDS layer 5, GDS datatype 0, description Niobium liftoff, color #6680b2)\n"
     ]
    }
   ],
   "source": [
    "print(ls['nb'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "advised-shift",
   "metadata": {},
   "source": [
    "We can quickly preview our color scheme using the pg.preview_layerset() function as well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "micro-paste",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "D = pg.preview_layerset(ls)\n",
    "qp(D)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "becoming-winter",
   "metadata": {},
   "source": [
    "### Making KLayout .lyp files"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "optional-count",
   "metadata": {},
   "source": [
    "We can even save the LayerSet as a KLayout .lyp file (\"layer properties\" file), useful for getting the color scheme in KLayout to match quickplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "surrounded-effects",
   "metadata": {},
   "outputs": [],
   "source": [
    "import phidl.utilities as pu\n",
    "pu.write_lyp('my_layer_properties_file.lyp', layerset = ls)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "maritime-sierra",
   "metadata": {},
   "source": [
    "### Ignoring layers with None\n",
    "\n",
    "In some cases, you may want to not use one of the layers for a given geometry.  PHIDL makes that easy by letting you pass `None` to any function that accepts layers.  For instance, say we have the following structure with three distinct layers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "efficient-manual",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def many_ellipses(layer1 = 1, layer2 = 2, layer3 = 3):\n",
    "    D = Device()\n",
    "    D << pg.ellipse(layer = layer1)\n",
    "    D << pg.ellipse(layer = layer2).movex(15)\n",
    "    D << pg.ellipse(layer = layer3).movex(30)\n",
    "    \n",
    "    return D\n",
    "\n",
    "qp(many_ellipses(layer1 = 1, layer2 = 2, layer3 = 3))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "downtown-certificate",
   "metadata": {},
   "source": [
    "Now say we want to remove the middle layer entirely.  We note that it's defined by the layer `layer2`, so we can set that to `None` and it won't be added at all:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "surface-procedure",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "qp(many_ellipses(layer1 = 1, layer2 = None, layer3 = 3))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "labeled-lending",
   "metadata": {},
   "source": [
    "## Removing layers\n",
    "\n",
    "We can remove the unwanted layers using the `remove_layers()` function.  Let's again start with our `pg.preview_layerset()` Device above:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "quick-basketball",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "D = pg.preview_layerset(ls)\n",
    "qp(D)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "interesting-graphic",
   "metadata": {},
   "source": [
    " Now let's remove layers 6 and 8.  This should leave us with just the gold (layer 4,0) and nb (5,0) layers. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "noticed-swiss",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "D.remove_layers(layers = [6,8])\n",
    "qp(D)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "stock-things",
   "metadata": {},
   "source": [
    "Whoops! Note that because we specified just an `8` as the layer we wanted to remove, PHIDL interpreted it as  `(8,0)`, so it didn't remove the the silicon layer that is actually on `(8,2)`.  Let's try again:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "differential-entrance",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "D.remove_layers(layers = [(8,2)])\n",
    "qp(D)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "prostate-lesbian",
   "metadata": {},
   "source": [
    "That's better.\n",
    "\n",
    "If we later decide that we actually **only** want layer 4, we can do that too.  To do so, we set \"invert_selection\" to True so that all layers **except** 4 are removed:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "improved-owner",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAe0AAAD7CAYAAABHTMzJAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAAAdlUlEQVR4nO3de5RddX338fc3mUiGTCbJTC4wBBMSckEQEIZHtLawxBbkEWWRp/XWirU29KnUXm29RSmiCFWfFkTbrILgpTzqAtsH7UoraxFbsaZGkUs04R4uk+tMmEsyk8xMfs8fc4acuSWZzJ5zss95v9baa835/fbl91179nxm77P3OZFSQpIkHf+mlHsAkiTp6BjakiTlhKEtSVJOGNqSJOWEoS1JUk7UlHsAhzN37ty0ePHicg/jmPT29jJt2rRyD6MkqqnWjo4O6uvryz2MkqiW/VotdYK15sVPf/rT3SmleaP1HdehvXjxYjZu3FjuYRyTlpYWmpqayj2MkqimWtetW8dll11W7mGURLXs12qpE6w1LyJi61h9Xh6XJCknDG1JknLC0JYkKScMbUmScsLQliQpJwxtSZJywtCWJCknDG1JknLC0JYkKScMbUmScsLQliQpJwxtSZJywtCWJCknxhXaEXFtRGyMiP0RceewvksiYnNE7IuIByJiUVFfRMRNEdFamG6OiMioBkmSqsJ4z7RbgBuAO4obI2IucC+wBmgANgLfLJplNXAlcA5wNvAW4JpjGrEkSVVqXKGdUro3pfTPQOuwrquATSmlb6eUeoDrgHMiYmWh/2rg8ymlF1JKLwKfB947kYFLklRtajJaz5nAw4MvUkp7I+KpQvvm4f2Fn88cbUURsZqBM3MWLlxIS0tLRkMsrba2tnIPoWSqqdb7v7+O/3zgu+UeRknMaZjPnrad5R7GpJt/8mJ+87feVe5hlEQ1HauVWmtWoV0H7BrW1g7MLOpvH9ZXFxGRUkrFC6WU1gJrAZqbm1NTU1NGQyy9PI99vKql1rbdLdz4gdPLPYySaOuupaG2vtzDmHS33PNs1fz+QvUcq1CZtWZ193gXMPzorgc6x+ivB7qGB7YkSRpbVqG9iYGbzACIiBnA0kL7iP7Cz5uQJElHbbyPfNVExHRgKjA1IqZHRA3wHeCsiFhV6P8E8EhKaXNh0a8CfxYRp0REE/DnwJ2ZVSFJUhUY75n2x4Fu4MPAbxd+/nhKaRewCvg0sAd4LfCOouX+AbgPeBR4DPheoU2SJB2lcd2IllK6joHHuUbrux9YOUZfAv6yMEmSpGPgx5hKkpQThrYkSTlhaEuSlBOGtiRJOWFoS5KUE4a2JEk5YWhLkpQThrYkSTlhaEuSlBOGtiRJOWFoS5KUE4a2JEk5YWhLkpQThrYkSTlhaEuSlBOGtiRJOWFoS5KUE4a2JEk5YWhLkpQThrYkSTmRWWhHRNewqT8ibi30LY6INKx/TVbbliSpGtRktaKUUt3gzxExA9gBfHvYbLNTSn1ZbVOSpGoyWZfH/xewE/jPSVq/JElVJ7Mz7WGuBr6aUkrD2rdGRAK+D3wopbR7+IIRsRpYDbBw4UJaWlomaYiTq62trdxDKJlqqrW+voG27jnlHkZJdB6oO/JMFWBOw/Tc/p0Zr2o6Viu11sxDOyJeCVwE/F5R827gAuDnQCNwG/AN4NLhy6eU1gJrAZqbm1NTU1PWQyyZPI99vKql1o6ONhpqG8o9jJJpqN1T7iFMuj1tHVXz+wvVc6xCZdY6GWfa7wF+mFJ6ZrAhpdQFbCy83BER1wLbIqI+pdQxCWOQJKniTMZ72u8B7jrCPIOXzWMSti9JUkXKNLQj4vXAKQy7azwiXhsRKyJiSkQ0ArcA61NK7VluX5KkSpb1mfbVwL0ppc5h7UuAdUAn8BiwH3hnxtuWJKmiZfqedkrpmjHa7wbuznJbkiRVGz/GVJKknDC0JUnKCUNbkqScMLQlScoJQ1uSpJwwtCVJyglDW5KknDC0JUnKCUNbkqScMLQlScoJQ1uSpJwwtCVJyglDW5KknDC0JUnKCUNbkqScMLQlScoJQ1uSpJwwtCVJyglDW5KknMg0tCNifUT0RERXYdpS1HdJRGyOiH0R8UBELMpy25IkVbrJONO+NqVUV5hWAETEXOBeYA3QAGwEvjkJ25YkqWKV6vL4VcCmlNK3U0o9wHXAORGxskTblyQp92omYZ03RsRngS3Ax1JK64EzgYcHZ0gp7Y2Ipwrtm4sXjojVwGqAhQsX0tLSMglDnHxtbW3lHkLJVFOt9fUNtHXPKfcwSqLzQF25h1AScxqm5/bvzHhV07FaqbVmHdp/BfwCOAC8A7gvIs4F6oBdw+ZtB2YOX0FKaS2wFqC5uTk1NTVlPMTSyfPYx6taau3oaKOhtqHcwyiZhto95R7CpNvT1lE1v79QPccqVGatmV4eTyltSCl1ppT2p5TuAh4ELge6gPphs9cDnVluX5KkSjbZ72knIIBNwDmDjRExA1haaJckSUchs9COiNkRcWlETI+Imoh4N/BrwL8B3wHOiohVETEd+ATwSEpp8+HWKUmSDsnyPe1pwA3ASqCfgRvMrkwpbQGIiFXAF4GvAxsYeM9bkiQdpcxCO6W0C7jgMP33MxDokiTpGPgxppIk5YShLUlSThjakiTlhKEtSVJOGNqSJOWEoS1JUk4Y2pIk5YShLUlSThjakiTlhKEtSVJOGNqSJOWEoS1JUk4Y2pIk5YShLUlSThjakiTlhKEtSVJOGNqSJOWEoS1JUk4Y2pIk5YShLUlSTmQW2hFxQkTcHhFbI6IzIh6KiDcX+hZHRIqIrqJpTVbbliSpGtRkvK7ngYuA54DLgW9FxKuL5pmdUurLcJuSJFWNzM60U0p7U0rXpZSeTSkdTCl9F3gGOD+rbUiSVM2yPNMeIiIWAMuBTUXNWyMiAd8HPpRS2j3KcquB1QALFy6kpaVlsoY4qdra2so9hJKpplrr6xto655T7mGUROeBunIPoSTmNEzP7d+Z8aqmY7VSa52U0I6IacA3gLtSSpsjog64APg50AjcVui/dPiyKaW1wFqA5ubm1NTUNBlDLIk8j328qqXWjo42Gmobyj2Mkmmo3VPuIUy6PW0dVfP7C9VzrEJl1pp5aEfEFOBrwAHgWoCUUhewsTDLjoi4FtgWEfUppY6sxyBJUiXKNLQjIoDbgQXA5Sml3jFmTYOLZLl9SZIqWdZn2l8GzgDelFLqHmyMiNcCLwFPAHOAW4D1KaX2jLcvSVLFyvI57UXANcC5wPai57HfDSwB1gGdwGPAfuCdWW1bkqRqkNmZdkppK4e/3H13VtuSJKka+TGmkiTlhKEtSVJOGNqSJOWEoS1JUk4Y2pIk5YShLUlSThjakiTlhKEtSVJOGNqSJOWEoS1JUk4Y2pIk5YShLUlSThjakiTlhKEtSVJOGNqSJOWEoS1JUk4Y2pIk5YShLUlSThjakiTlRElDOyIaIuI7EbE3IrZGxLtKuX1JkvKspsTbuw04ACwAzgW+FxEPp5Q2lXgckiTlTsnOtCNiBrAKWJNS6kop/RD4f8DvlGoMkiTlWSnPtJcD/Smlx4vaHgYuKp4pIlYDqwHmz5/PunXrSjfCDLW3tzNr1qxyD6MkqqnW3v6pfOS2J8s9jJKor2+go6Ot3MOYdA1zm3L7d2a8qulYrdRaSxnadUD7sLZ2YGZxQ0ppLbAWoLm5OV122WWlGV3GWlpaaGpqKvcwSqKaagXI6+/keFXLfq2WOsFaK0Epb0TrAuqHtdUDnSUcgyRJuVXK0H4cqImIZUVt5wDehCZJ0lEo2eXxlNLeiLgXuD4i3s/A3eNvA15fqjFIGqq/v5/9+/cPaZs2bRrTpk0r04gkHU6pH/n6Q+AOYCfQCvxvH/eSyufLX/wCjz70H0ydMnDRLaXEtNpGbvnSV8o8MkmjKWlop5TagCtLuU2p2qWUePLJJ+nu7h7Rt3vXNn77zSez/LS5APT1HeSv124GoKOjg927dw+Zv7a2lmXLlo1YD8Czzz5LR0fHkLbGxkZOOeWULMqQROnPtCWVUH9/P9/42ld4ZMN9zGs4YUT/DPqZ23DqqMv+14M/4MmHv0v9zNqX2554oZe/v/3b1NSM/NNxyxeup7G2nZqaqQB09xxg6ozTWXP95zKqRpKhLVWo7u5uvvTFz3OgdSN/9K4VTD9hfId7Sge5uHkeZ6886eW2Nbc9Skpp9Pn7D/D2Sxczs27gn4Pnt7XzvZ/0HnsBkkYwtKUK1Nrayt9+7q85deZ2rrjyDKZMiXIPSVIGDG2pwjz99NN88QvX8SuvOsgbmk8v93AkZcjQlirI448/zq2f+whXXTSHVy2bP6TvqedaeXjz0I8lnRLwxtedSn3d9FIOU9IxMrSlCrJlyxaal8WIwN7y9G7uWd/OW1at5hWveMXL7f/+r/ewfVeXoS3lhKEtVZjh718//sxAYH/wQ59h6dKlQ/r++0f3s33XLmqmDjyn3X9w9JvMJB0fDG2pwt2/oZX3XvPxEYENsPLM1/DYw708uedQ22uaV5ZwdJLGw9CWKtzBFMyZM2fUviveehVXvPWqEo9I0rEytKUKVzPlIC+88AKLFy8e0feNr93BQz/5wZC2WY1NrPnkjWOsK/Hiiy+OWFdrays93fuYMtVHy6TJVMpv+ZJUBldc3MS3vvp5fvazn43oa3nhGS55TfD7b23g99/awHsvn83zz/xyzHWtumQB/+emj/Lcc8+93Nba2spNN3yY37hgBjNqXzHmspImzjNtqcL09h0c8vqUBfW89wq48+8/xZaLVw25e3zXrl3ULXkFs+sHPqq0b9iyfX39Q16ftXwBsIPP3/hhfvWNbyMi2PDg93nd8h5ef/7oH4cqKTuGtlRBzj77bL7wvRpOX7SbFUvmvtx+yoJ63n/lFDY9cR8HiuY/f3Gw8OTRw3bZijO55+vrOOWkWSyYW/dy+1nLF1A7vZWtL94LwGXn13HmcgNbKgVDW6ogixYt4oMf+gy3/M1HWQVDgnvB3Loh4XskS5eezjt+98Pc8ZXP8r63LRqy7NJXNrL0lY1D5u/Z3zfuzzeXND6+py1VmKVLl/LBD32Ge9a3s+Xp3Ude4DAuvPB1A8H9L1vZsbtrzPke3bKd67+0gb3dB8acR9LEGdpSBSplcD+6ZTv3/aiHaSfO52C/H84iTSavZUkVajC4/+5vPs6MH7Ue1TIpJWpeMWNE+4UXvg74MGv/8WZmnjj0f/3uvlr+/COf5dYv3MDae59m6pSB/t6+fuYsOGPCdUg6xNCWKtjSpUu54eZ/oLOz86iXmT599M8hv/DC17Fs2T/S09MzpL2+vp6ZM2fy0U/exL59+4b0zZw5c/yDljQmQ1uqcPX19dTX12eyrsbGxjH75syZM+Ynr0nKxoTf046IEyLi9ojYGhGdEfFQRLy5qH9xRKSI6Cqa1kx0u5IkVZsszrRrgOeBi4DngMuBb0XEq1NKzxbNNzul1JfB9iRJqkoTDu2U0l7guqKm70bEM8D5wLMTXb8kSRqQ+SNfEbEAWA5sGta1NSJeiIivRMTcURaVJEmHkemNaBExDfgGcFdKaXOheTdwAfBzoBG4rTDPpWOsYzWwGmDhwoW0tLRkOcSSaWtrK/cQSqaaam1vb8/t7+TROHjwIP/6vX9mf08XtSfOpHvfwF3npy87i3POPa/Mo5sc1fT7a635d8TQjoj1DLxfPZoHU0pvKMw3BfgacAC4dnCGlFIXsLHwckdEXAtsi4j6lFLH8BWmlNYCawGam5tTU1PT0VdznMnz2MerWmqdNWtWRde6c+dOfvmz+3n7b5xETyxgesMOfv6LbezZc3JF113JtQ1nrfl2xNBOKV18pHkiIoDbgQXA5Sml3sOtcnCxoxmgpNLZuXMn8+ZM47RTG2jrrqOhtpeHN7ex4KSF5R6aJLJ7T/vLwBnAFSml7uKOiHhtRKyIiCkR0QjcAqxPKbVntG1JGdm5cyeNM4f+P93aeZAFCxaUaUSSimXxnPYi4BrgXGB70bPY7y7MsgRYB3QCjwH7gXdOdLuSsrd92/M0zh56Aa6t4yDz5s3LZP0pJbq7u0dMvb2HLs719PQMeS3pkCwe+drKYS51p5TuBu6e6HakSvbBD7yPrvadQ9rqZs3nltvuOOx8o80zETtatnJu04kvv+7rO0jHvn7mzp34Ax+9vb3c+nc38/imHxNFfzIOpsT8pmV86jNf4Je//CWfv/HD1NaeyAf/4nqWLVs24e1KlcSPMZWOA13tO7nxg2cPafvILY8ccb7R5pmIHdueY95Zh74wZE97Nw0N85g6deqE1tvb28stf3sTU7t+xievOYspUw6F9k8ffZFn9w3cMPTYYw9z8bnTWXTKTG793Mf4o7/4tMEtFfGrOSUB0N/fT1vbLubMqn25bVfbXhac/MoJrbc4sN/+5hVDAhvg6ZZ9nHHW+QBsfuwnLH3lHJafNpfffONsbv3cx3jiiScmtH2pkhjakgBobW2l/sSp1NQc+rPQ+tI+FjQtOuZ1HimwAZ7d1seKFSvo6emh5bmnOLVpFoDBLY3C0JYEDNw53lA/9DJ460t9x/y4V19f35iB3dd3kEc2b+fHDz1PHydy8skn8+STT9I0r4ZpNYfGUBzcTz311LEVJlUQQ1sSkP3jXi0tLWx/5iejBvY/fXcLG56ex/b+83jrVVcTEZx44ons2tPPC9uHPg26/LS5/Oqrp/IfD/z7MY1DqiTeiCYJyP5xr5QSJ5wwbdTArl3wev70A39KTc2h7S1ZsoTf/cNP8JUvXc/VV8DCk2a93Fc7fRqd6eAxjUOqJJ5pSwIGHvdqnH3oca/+gymzx70G/ddDzzFldjN/MCywB73mNa/hPdd8jH/61+cy26ZUSQxtSUDhca+GQ497de07kMnjXsW69/eybOWrRw3sQStWrOBAX3bblCqJoS1p1Me9Ojp7Jvy4l6RsGdqSRn3cq3Pv/gk97iUpe4a2pFEf9+rcd9Bv95KOM949Lh2nTpjaw/t++y0j2saaZyKfQz7a415d3clv95KOM4a2dJy67gP/Y1zzTORzyLdve56GWSPPtLP6di9J2fDyuCR2tGxl7pxDd4739R2k+8DBTB/3kjRxhrakEY977Wnvpq6uPtPHvSRNnKEtVbmxvt1r1pzJuTS+f//+w/YfOHAASJOybSnvfE9bOg7UzZp/VO9JnzC1Z8j72Nfd9t/s75/+8jqOxVjf7jW7MfvQPnvFSdz+L//E0qVLOe+880b07927ly/+7Y00r6wdZWlJhrZ0HDjau76H302+v386d3z9uxPa9ljf7rX49MYJrXc0J82byXuvOIU7//5T8AdrOO+88+jr62Pr1q309/dz99fWcurM57n0V5dkvm2pEnh5XKpyoz3u1daZmDVr1hhLHJ1Zs2bR0V3D5qd3DWk/ZUE9V7xhDuvu+78AbNiwgVtv+hPuXvtRTm9s4fKLlhBxaDw9+/v4yaZ2Fpx86oTGI1UCQ1uqcqM97tXa0T/h0J49ezZ//KFPc88D7SOCu/WlbpYsPxuAXzz6U97YPJs/+K3lvOn1i0cE9h33bmHpOW/l8v95xYTGI1WCTEI7ItZHRE9EdBWmLcP6L4mIzRGxLyIeiAg/G1E6Toz2uFfHvn5mzpw54XUvXbqUP/7LG0cE9zPbell5xlmklNi86acseWXDiGWLA/t3rn7fkDCXqlWWZ9rXppTqCtOKwcaImAvcC6wBGoCNwDcz3K6kCRjtca+GhnlMmZLNn4fhwd3ff5Dndhxg2bJl7Nq1i/4D7cydc+KQZQxsaXSluBHtKmBTSunbABFxHbA7IlamlDaXYPuSxnDoca9DH6Kyq21v5t/uNRjcf3fzR1h20g7mn7SYGTNm8NBDDzHlYBfrfvDkkPmfaulh2blXGtjSMFmG9o0R8VlgC/CxlNL6QvuZwMODM6WU9kbEU4X2EaEdEauB1QALFy6kpaUlwyGWTltbW7mHUDLVVGt7e3tZfydPW3YOt9zTPuT1RMbT3t7OaYtPo6O3EXoH2tp6emk69fTM92ttbS3v/8DHef7557lw/nxaWlpoaGjgkiv/dMS8p54/nZUrV7Jt27ZMxzCaavr9tdb8yyq0/wr4BXAAeAdwX0Scm1J6CqgDdg2bvx0Y9Q2zlNJaYC1Ac3NzampqymiIpZfnsY9XtdQ6a9assta65pOfznR9bW1tpJ4Xaag9dHl69/atnH7hZTQ0NGRea1NTE2efffaQ16961asy3caxqJbfX7DWvDvim1aFm8zSGNMPAVJKG1JKnSml/Smlu4AHgcsLq+gC6oetth7ozLIQSeM31uNefruXdHw64pl2SuniY1hvAgb/EmwCrh7siIgZwNJCu6QyGutxr3nz5tHf31+mUUkay4Qvj0fEbOC1wA+APuDtwK8Bf1KY5TvA30TEKuB7wCeAR7wJTSq/l9p28/ijXTz0xOMvt3Xtn0ZjYyM7d+4s48gkjSaL97SnATcAK4F+Bm4uuzKltAUgpbSrENhfBL4ObGDgfW9JZfae372Gl156+5C22tpaamr8hGPpeDThIzOltAu44Ajz3M9AqEs6jtTV1VFXV1fuYUg6Sn6MqSRJOWFoS5KUE4a2JEk5YWhLkpQThrYkSTlhaEuSlBOGtiRJOWFoS5KUE4a2JEk5YWhLkpQThrYkSTlhaEuSlBOGtiRJOWFoS5KUE4a2JEk5YWhLkpQTkVIq9xjGFBG7gK3lHscxmgvsLvcgSsRaK1O11FotdYK15sWilNK80TqO69DOs4jYmFJqLvc4SsFaK1O11FotdYK1VgIvj0uSlBOGtiRJOWFoT5615R5ACVlrZaqWWqulTrDW3PM9bUmScsIzbUmScsLQliQpJwxtSZJywtCeoIi4NiI2RsT+iLhzlP5LImJzROyLiAciYlFRX0TETRHRWphujogoaQETEBHrI6InIroK05Zh/WPWnjcR0RAR34mIvRGxNSLeVe4xZeVw+zHP+/Bwx2alHZdj1RoRiyMiFe3brohYU9Sfx1pPiIjbC8dhZ0Q8FBFvLuqvqH07nKE9cS3ADcAdwzsiYi5wL7AGaAA2At8smmU1cCVwDnA28BbgmskdbuauTSnVFaYVg41HUXve3AYcABYA7wa+HBFnlndImRqxHytgH456bFbocTnm36GC2UX791NF7XmstQZ4HrgImMXAfvxW4R+USty3Q6WUnDKYGDhg7hzWthr4UdHrGUA3sLLw+kfA6qL+3wN+XO5axlHzeuD9Y/QdtvY8TYWxHwCWF7V9Dfhsucc2mfuxUvbh8GOzko/LUWpdDCSgZoz5c1vrsDoeAVZV8r4dnDzTnlxnAg8Pvkgp7QWeKrSP6C/8nLeztxsjYndEPBgRFxe1H6n2PFkO9KeUHi9qy+O+OpzR9mMl7cNi1XBcDrc1Il6IiK8UzkYH5b7WiFjAwDG6iSrYt4b25KoD2oe1tQMzx+hvB+py9B7LXwFLgFMY+CCD+yJiaaHvSLXnSSXVMpqx9mOl1l3px2Wx3cAFwCLgfAZq/EZRf65rjYhpDNRzV0ppM1Wwbw3twyjcoJPGmH54FKvoAuqHtdUDnWP01wNdqXDdppyOpvaU0oaUUmdKaX9K6S7gQeDywiqOVHueVFItIxxmP1Zq3bk9LscrpdSVUtqYUupLKe0ArgV+IyIG68ttrRExhYG3qQ4wUBdUwb41tA8jpXRxSinGmN5wFKvYxMANDwBExAxgaaF9RH/h500cB46x9gQM/sd6pNrz5HGgJiKWFbUdN/tqEgzux0rah8Vye1xmYDCcRj1OyUmthTPj2xm4MXRVSqm30FXx+9bQnqCIqImI6cBUYGpETI+ImkL3d4CzImJVYZ5PAI8ULuMAfBX4s4g4JSKagD8H7ixxCcckImZHxKWD9UbEu4FfA/6tMMuRas+Nwvti9wLXR8SMiPgV4G0M/Jefa0fYj7neh4c5NivuuByr1oh4bUSsiIgpEdEI3AKsTykNXiLOXa0FXwbOAK5IKXUXtVfcvh2h3HfC5X0CrmPgv9fi6bqi/jcBmxm4g3E9sLioL4CbgbbCdDOFz4M/3idgHvATBi47vQT8GPj1YfOMWXveJgYeH/lnYC/wHPCuco+pFPsxz/vwcMdmpR2XY9UKvBN4pvB7u42B0Dop57UuKtTXw8Dl7sHp3ZW4b4dPfmGIJEk54eVxSZJywtCWJCknDG1JknLC0JYkKScMbUmScsLQliQpJwxtSZJywtCWJCkn/j+UyZrUBv+G0wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "D.remove_layers(layers = [4], invert_selection = True)\n",
    "qp(D)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "identical-establishment",
   "metadata": {},
   "source": [
    "## Remapping (moving) layers\n",
    "\n",
    "\n",
    "We can use the `remap_layers()` function to map layers arbitrarily. We'll start again with our layerset_preview device:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "educated-viking",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "D = pg.preview_layerset(ls)\n",
    "qp(D)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "average-butler",
   "metadata": {},
   "source": [
    "Now say that we wanted to move shapes on the silicon layer `(8,2)` to layer 99, and nb_etch layer `(6,0)` to layer 77 but leave the other layers alone.  We do this by construction a python dictionary and passing to `remap_layers()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "intellectual-account",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "D.remap_layers(layermap = {(8,2): 99,\n",
    "                             6  : 77,\n",
    "                           })\n",
    "qp(D)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "reverse-center",
   "metadata": {},
   "source": [
    "Very good!  We can see from the colors of the bottom polygons changing that the layer remapping worked."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "regulation-closer",
   "metadata": {},
   "source": [
    "## Extracting / copying layers\n",
    "\n",
    "### Extracting layers\n",
    "\n",
    "Say you want to access or copy all the polygons of specific layer(s) from an existing Device. You can do this using the `pg.extract()` function, which will copy layers out of one Device and put them into a new Device.\n",
    "\n",
    "Let's start with a Device with a few objects in it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "general-percentage",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "D = Device()\n",
    "\n",
    "D << pg.ellipse(layer = 1)\n",
    "D << pg.rectangle(size = (10,10), layer = 2).movex(15)\n",
    "D << pg.arc(width = 10, layer = 3).movex(25)\n",
    "D << pg.circle(radius = 5, layer = 2).movex(50)\n",
    "\n",
    "qp(D)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "graphic-collect",
   "metadata": {},
   "source": [
    "Next, let's use `pg.extract()` to create a new Device which only has the objects on layers 1 and 2:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "celtic-somerset",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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RcsYPu47JZRdrz9pjOdnDmTZxLlmdH+f66x7ijtvvobm52e+yRELHOcfPfvITSltbOTbFs/r1xxFjxnCUGT+9/Xacc36X028K7QHgnOPFF1/iC5/9Hjve+xBHTfoSuQeZOUy8MWLoVKZPvJ5XnsnjS5+/haqqqkN/koj02pIlS3jv5Zc5d0rw3pzxtIoK9qxYwfPPPed3Kf2m0PZYZ2cnP7n75/z3rc8xftiXKS0+RfcXp0gsmsmUCZcRbbucr37pbp555nm/SxIJhZaWFh686y4uqqjo13SkfolEInxkyhR+e8897Nmzx+9y+kWh7aHm5mZuuemHPPtEG9PLryMvZ4zfJaWl0SOOZtKY67jzthe4/76HSCaTfpckEmiPP/ooE4FxQ4f6XUqfjcjLY0Z2NoseftjvUvpFoe2R5uZmrp9/G2veGs+0iVcTi6Z+ViD5myHZwzhywldZ9NAW7v7xvQpukT7as2cPLzz6KGcMwDziqTa7vJylTz/N9u3b/S6lzxTaHmhpaWHB9f/NtvemMbnsUh0OHyQyM4YwbeI8nvnDHn668L5QXIQikmpPP/UU03NyyAvBfN7xjAwqCwp48vHH/S6lzxTa/ZRMJrntez9h87uTqBh/sQJ7kIlFM5k24bM89dgOFi36vd/liARKIpHghccf56TSUr9L8czxpaX85emnaWlp8buUPlFo99PDDy3izSXG5AmXKbAHqVgsiymln+a+e15m2bJlfpcjEhhvvfUWo5xjaE6O36V4JjceZ0JmJkuWLPG7lD5RaPfDO++8w0MPLGVq2acG5Xtay9/Es/IpG3k1//Wd+2loaPC7HJFA+MvzzzO9qMjvMjx31PDhLAno7V9Kmj5KJBLc8cNfMrrgo2RmhOev0DArKpgAbSdx/32/8bsUkUEvkUiw6vXXmTomfHfBVIwaxYZ33gnkREwK7T565pnn2bFlDKNHHO13KXIYJpZcwNNPrg3VXMQiA2HDhg0Mi0QY4sP7Yw+0jGiUknictWvX+l3KYVNo90EymeThXz3LuJEf9rsUOUyxWBYF8bP53aPP+F2KyKC2bt06SkJwxfjBjIvHWafQTg8bNmygqXYkBXnBmX9X/mbc6JP50+LVNDU1+V2KyKBVvWYNY3Jz/S5jwBQXFFC9erXfZRw2hXYfvPP2BvKzT/S7DOmjjFicTDua6upqv0sRGbS2VlczMi/P7zIGzIi8PGo2bvS7jMOW0tA2s6FmtsjMms2s2syuSOX4XnDOUbVuC8OLpvpdivRDbnwq697d4ncZIoPW7p07KRwyxO8yBkxBdjb1dXWBmy0x1XvadwIdwCjgSuAuM5uW4hr6ZefOnbS3RRmSPXjf/F0ObVhhBRurt/ldhsig1NXVRWtzcygvQtsrGomQFYkE7grylIW2meUAc4BvOueanHMvAY8BH0tVDV5oaGggGtEtXkEXzyqkublNU5uKHEB7ezsZkUjoJ4zKjEZpb2/3u4zDEkvhWJOBLufcvpfrLQNm7/skM5sLzAUYOXIkTz75ZOoq7IUtW7bQ0VFLA4OrLq/VNb3pdwkDLuGaeeyxx8jKykrZmPHhw1nw+uspGy+/qIiGurqUjQfdPab657a+vp6CgoKUjplqqeyxvb0dF4/zSm1tSsbbq7WpieyOjpSNl8jMZPHixeSm8IK7/m7HVIZ2LlC/37J64O+udHDOLQQWAlRWVrpzzz03NdX10vLly1m9/DVybXDVNRDys8LdY2fnUs4++2yys7NTNmaqv59ramooLi5O6Zh+SIc+U9lja2srT9x3Hyen+K049+TmUpjCuzqWVFVx2mmnMWxY6k539nc7pvKcdhOQv9+yfKAxhTX0W15eHkmCOdG8/E1XVwKzLuIhvg9VpK+ysrJIJJOBu0jrcLV1daX0j3YvpDK01wIxM6vYZ9kMYFUKa+i3oqIiOrsadS404Jpbd5JXkBP6c3YifRGJRMjNy6MpYOd7D0eiq4suUGgfjHOuGXgEuNHMcszsg8BFwP2pqsELhYWFFBRm0dCk24WCbHfdGsrLw304VaQ/ho8aRV1A376yN+qamxk6cmTg/nBP9S1fnwGygR3Ag8A1zrlA7WkDVEwey866t/0uQ/qhtfMdJkwc63cZIoPW2PJytof4HfF2NDQwtqzM7zIOW0pD2zlX65z7iHMuxzk33jn3y1SO75UjjpxEc8dLOkQeUK1tdZDxLqWlpX6XIjJoTZg8ma0Bu4f5cGxuaGDCEUf4XcZh0zSmfTBmzBjKJmWyY3fgDhIIsGnbYi648EQyQzxxhEh/TZo0ieq2Nr/LGDCb2tupmDzZ7zIOm0K7D8yMK646l611i0i6cF9dGTatbXW08yfOO/8Mv0sRGdRKSkpIxOPUhXBvu6Wjg11dXZSXl/tdymFTaPfRzJkzOfb4XKprnve7FDkM62se4sqPn8bw4cP9LkVkUItEIhx78smsqqnxuxTPvVNTw/TjjiMjI8PvUg6bQruPzIyrP30FLV1P0NAUvm/qMNq07S+MKqnhggvCPWmMiFdOnDWLFfX7z4kVfMvr6jjptNP8LqNPFNr9MGrUKL70lX+mquYuOhLhvTUiDPY0bKQx8Wu+Nv/TgfzrWsQPU6dOJVlUxKYUT2c6kHY0NlKbkcGMGTP8LqVPFNr9dNJJJzLn8um8897ddHalbs5c6b3m1l1s2P5jvvK1K0I/1aWIl8yMs+fM4eVNm/wuxTN/rq7mzIsvJhZL5Sze3lFoe+DKq/6ZM88v5J31d9HVlfC7HNlHS+tu1m6+jS98+TwqK2f6XY5I4JwyaxZbolG27tnjdyn9VtvczJpEgjPOOsvvUvpMoe2BSCTCp6/5BLPPyWHl+h/RkQjf1ZZBVN+4mTWbv8dnv3gmp502+9CfICL/ICsri4s+9jGeWr8+8HNTPL1uHef+y7+QkxPct1dWaHskEonw2Xn/xqVXlrJqw3dpatnhd0lpbfuulWza/QO+fsMlnHXW6X6XIxJop552Gp2jR7Ni82a/S+mzddu3szMnh3POO8/vUvpFoe2hSCTCFVdcyhe/eiYbtn+XLdtf87uktJNMdvFu9aO0Ru/n1u9fw/HHH+d3SSKBF41G+eTnPsdTNTU0BnDClbZEgsffe49PfP7zgZ9USaE9AE49dRa33f4FMgoe4+319+rK8hRpbN7GiqrvcWTlRn50x/xATpwgMlhNnDiRMy6/nN+uWhWot+x0zrFo1SqO+/CHmTZtmt/l9JtCe4CMHz+e7//gG5x/SZy3qxewZfvSwJ8PGqy6kp1UbXqCzXv+H/P+8wS+9vXPkZeX53dZIqFz0SWXkDN9On9cs8bvUnrthXXr6Bg/nsuuuMLvUjyh0B5A8Xicj3/icr73w6vJHfUHVlR9nz0N1X6XFRrOOWp2vMGKqhs46oT3+PFPvsHpp58auLfaEwmKSCTCNV/6Eu/l5vLnDRv8LueQ3ti4keXA56+9NjTzMyi0U6C8vJzv3fYNvvDVE9jdfger1i/ULGr94Jxjx+5VrKi6lZyR/8d3vv8xvvLVzzB06FC/SxMJvZycHL58ww281tnJkkEc3Ms2b2ZxYyNf/ta3KCws9LsczwTz7vIAikQizJp1CieccDzPPfcCD9x3G5t2TGLMsLMZWjDR7/ICIemSbNvxJrsa/0hxaTtf+8IFzJw5U3vWIik2bNgwrrvlFv7r+utpWbuWUysqBtXP4Z83bODV9nau/fa3GTNmjN/leEqhnWJZWVmcd97ZnH76bF5++RUe+uU9rKjKpXDIqRSPrCQaDcchHC+1dzSyedvLNCVeZOq0Qq65/DxmzJgxqH5JiKSbESNGMP/WW/nBt7/Nb5Yv58Jp08jyeZaxRFcXT7zzDjuKivj6jTeG8o2BFNo+ycrK4vTTT+PUU2ezcuVKHv/dYpa++mvikZmMLDqRooKJaR1KXV0JduxeSV3TX0jG1nDWOR/gnHOvprS01O/SRKRHQUEBX7vpJn7xs5/xk6ef5uKKCsb5dJpqe309v12zhvEnn8z8a64hHo/7UsdAU2j7LBKJcPTRR3P00UdTV1fHyy//hSefuJ9lVW1kR2cyvPAYigrLiVj4Lz/o7OpgZ+3b7Gl6k/bkcqYfXcLHzj+RmTM/GdofQJGgy8zM5N+uvppXjz2WX9xxB1O3beOMigriKbrwq72zkxerqljW2so/z5vHKbNmhXqHR6E9iBQVFXHBBedxwQXnUVNTw2uvvcHzz/yK5VV1ZEWPJCfrSEYMPYLseJHfpXrCOUdjcw276lbT1rWKRHIdR8+YwGWnHcMHPnBxqC4eEQm7448/niPuvJPf/upX/Oippzhp2DCOLysbsEPmia4uXquu5s+7djFt9mxuuuqqtPidkZLQNrPFwIlAZ8+iLc65KakYO6iKi4u56KJiLrroAurq6li5ciWvvbqS11/7Da0t2WTZJOKZ5RTlTyAvp5hIJOp3yYfU2dlOfeNG6ho3kOiqor1rHSNGxZl17hEcO/NDHHHEp8jOzva7TBHpo7y8PD7xqU9x9j/9E4/95jf84MUXOSovj5ljxzKqoMCTMXY1NfH6pk0sa2hgyvHH85/XXZdWp81Suac9zzn3PykcLzSKioo45ZRTOOWUU3DOsXXrVtatW8fKletZuexZ1q+vJTM6hpiVEIsUk5czhpwho8iOD/XlsHpXV4KWtl00NW+jsWUrSbaQcJtJspuJ5WM56/QJTD1iJhUVl1NUFI6jBiLyN8XFxXz6859n1xVX8OLixTz05JNE3n2XSTk5lA8dSklREdm9nE60LZFgc10dG2prWdfSQmtWFh885xyuP/10Ro0aNcCdDD46PB4wZkZxcTHFxcXMmjULgPb2djZv3syWLVt4b0MNVetWsLF6O7VbGsmIFBGLDsMoxJKFZETzycrMJyMjh4yMIcSicWKxONFIJpFIjEgkhtF9Psg5h3NJkslOkq6Tzq52Ojvb6OxsJdHZQkeimfaOBjqT9WB7SFJHIrkbRxOjRg9j/JGjmDR5DOPHH0VJyXmMGTOGaHTwHxEQEW8MHz6cSy69lIvnzGHDhg2sWLaM115/nd8sX04cGJqZSV4kQjwSIeYcWcXFtGzdSptzNHZ1UdvRQbNzlE6axJHnn8/so4+mvLycSCT81/gcjKVias2ew+PTAAPWAN9wzi0+yHPnAnMBSkpKZi5ZsmTA6ztctbW1gZjIo6uri6amJhobG2lqaqKlpYWGhhYaG9poaW6jtbWdtrYOOjoSJBKdJJNJurqSOJck0dlIRiwPswjRaIRYLEpGRgaZmRnE45lkZ2eSk5tNfn6cvPwchgwZQk5ODnl5eeTm5gbiQpCgbMf+SIceIT36DFOPzjkaGhpoaGigubmZ9vZ2Ojs7cc4Ri8XIysoiJyeHgoIC8vLyQhXSvdmOY8eOfd05V3mgdana074WeBvoAC4HHjezY5xzVfs/0Tm3EFgIUFlZ6YqLi1NU4uEZrHV55Q9/+APnBfwt7Hoj7NsR0qNHSI8+w9Tj2LFj/2FZTU1NqHo8mP702O8/X8xssZm5gzxeAnDOLXHONTrn2p1zPwdeBs7v79gycIKwpywikm76vaftnDu1L58GKBVEREQOw4CfKDCzQjM7x8ziZhYzsyuBWcBTAz22iIhImKTinHYGcDMwFegCVgMfcc4F5w1ZRUREBoEBD23n3E7guIEeR0REJOzCcx29iIhIyCm0RUREAkKhLSIiEhAKbRERkYBQaIuIiASEQltERCQgFNoiIiIBodAWEREJCIW2iIhIQCi0RUREAkKhLSIiEhAKbRERkYBQaIuIiASEQltERCQgFNoiIiIBodAWEREJCIW2iIhIQCi0RUREAsKT0DazeWa21MzazezeA6w/w8xWm1mLmT1vZqVejCsiIpJOvNrTrgFuBv53/xVmNhx4BPgmMBRYCjzk0bgiIiJpI+bFizjnHgEws0qgZL/VlwCrnHO/7nnOAmCXmU11zq32YnwREZF0kIpz2tOAZXs/cM41A1U9y0VERKSXPNnTPoRcYOd+y+qBvAM92czmAnMBSkpKqKmpGdjq+qC2ttbvEgZcfX39oPzaeykdtmM69Ajp0ad6DIf+9njI0DazxcDsg6x+2Tn3oUO8RBOQv9+yfKDxQE92zi0EFgJUVla64uLiQ5Xoi8Fal1cKCgpC3yOEfztCevQI6dGnegyH/vR4yNB2zp3a51fvtgr4+N4PzCwHKO9ZLiIiIr3k1S1fMTOLA1EgamZxM9v7B8EiYLqZzel5zvXAcl2EJiIicni8uhBtPtAKXAdc1fP/+QDOuZ3AHOAWoA44Abjco3FFRETShle3fC0AFrzP+meAqV6MJSIikq40jamIiEhAKLRFREQCQqEtIiISEAptERGRgFBoi4iIBIRCW0REJCAU2iIiIgGh0BYREQkIhbaIiEhAKLRFREQCQqEtIiISEAptERGRgFBoi4iIBIRCW0REJCAU2iIiIgGh0BYREQkIhbaIiEhAKLRFREQCQqEtIiISEJ6EtpnNM7OlZtZuZvfut67MzJyZNe3z+KYX44qIiKSTmEevUwPcDJwDZB/kOYXOuU6PxhMREUk7noS2c+4RADOrBEq8eE0RERH5e17tafdGtZk54GngK865XQd6kpnNBeYClJSUUFNTk8ISe6e2ttbvEgZcfX39oPzaeykdtmM69Ajp0ad6DIf+9piK0N4FHAe8BQwD7gQeoPtQ+j9wzi0EFgJUVla64uLiFJR4+AZrXV4pKCgIfY8Q/u0I6dEjpEef6jEc+tPjIS9EM7PFPReSHejx0qE+3znX5Jxb6pzrdM5tB+YBZ5tZfp+rFhERSUOH3NN2zp3q8Ziu51/z+HVFRERCzZPD42YW63mtKBA1szjQ6ZzrNLMTgD3Au0AR8CNgsXOu3ouxRURE0oVXk6vMB1qB64Crev4/v2fdROBJoBFYCbQDH/VoXBERkbTh1S1fC4AFB1n3IPCgF+OIiIikM01jKiIiEhAKbRERkYAw59yhn+UTM9sJVPtdxwEMp/v+8zBTj+GQDj1CevSpHsOhNz2WOudGHGjFoA7twcrMljrnKv2uYyCpx3BIhx4hPfpUj+HQ3x51eFxERCQgFNoiIiIBodDum4V+F5AC6jEc0qFHSI8+1WM49KtHndMWEREJCO1pi4iIBIRCW0REJCAU2iIiIgGh0O4lM5tnZkvNrN3M7j3A+jPMbLWZtZjZ82ZW6kOZ/WZmQ81skZk1m1m1mV3hd0399X7bLkTbLcvM7unZZo1m9qaZnbfP+rD0+Qsz22pmDWa21sz+Y591oehxLzOrMLM2M/vFPstC0aOZLe7prannsWafdaHocS8zu9zM3un5nVplZqf0LO9Tnwrt3qsBbgb+d/8VZjYceAT4JjAUWAo8lNLqvHMn0AGMAq4E7jKzaf6W1G8H3HYh224xYBMwGyigu6eHzawsZH1+ByhzzuUDFwI3m9nMkPW4153Aa3s/CGGP85xzuT2PKRC+Hs3sLOC7wCeBPGAWsL5ffTrn9DiMB92//O/db9lc4JV9Ps6h++1Jp/pd72H2lkN3YE/eZ9n9wK1+1zYQ2y4s2+19+l0OzAlrn8AUYCtwWdh6BC4HHqb73RN/0bMsND0Ci4H/OMDy0PTYU/8rwL972af2tL0xDVi29wPnXDNQ1bM8SCYDXc65tfssW0bw+uitsGy3f2Bmo+jenqsIWZ9m9mMzawFW0x3aTxCiHs0sH7gR+M/9VoWmxx7fMbNdZvaymZ3asyw0PZpZFKgERpjZOjPbbGZ3mFk2/ehToe2NXKB+v2X1dB8OCZKw9NFboezXzDKAB4CfO+dWE7I+nXOfobv2U+g+xNhOuHq8CbjHObdpv+Vh6vFaYCIwlu7JRh43s3LC1eMoIAO4lO7v1WOAY4H59KNPhTZ/vSjCHeTxUi9eognI329ZPtDofbUDKix99Fbo+jWzCN2nNDqAeT2LQ9enc67LOfcSUAJcQ0h6NLNjgDOB/z7A6lD0COCcW+Kca3TOtTvnfg68DJxPiHqk+3A3wO3Oua3OuV3AbfSzT4U24Jw71TlnB3l8qBcvsQqYsfcDM8sBynuWB8laIGZmFfssm0Hw+uitsGw3AMzMgHvo/gt/jnMu0bMqVH3uJ8bfeglDj6cCZcBGM9sGfBmYY2ZvEJ4eD8QBRoh6dM7VAZvp7m1/fe5Tod1LZhYzszgQBaJmFjezWM/qRcB0M5vT85zrgeU9hyYDo+e8yiPAjWaWY2YfBC6ie88tsN5n24Viu+3jLuAI4MPOudZ9loeiTzMb2XP7TK6ZRc3sHOCjwHOEpEe6DxWX030o9RjgbuD/gHMISY9mVmhm5+z9OTSzK+m+qvopQtLjPn4GfK7ne7cI+CLwe/rTp99X1wXlQfdVnG6/x4J91p9J94UxrXRfGVnmd8197HMo8CjQDGwErvC7poHcdiHabqU9fbXRfeht7+PKsPQJjABeAPYADcAK4FP7rA98jwfoeQE9V4+Hpcee7fga3YeC9wB/Ac4KU4/79JIB/Linz23Aj4B4f/rUG4aIiIgEhA6Pi4iIBIRCW0REJCAU2iIiIgGh0BYREQkIhbaIiEhAKLRFREQCQqEtIiISEAptERGRgPj/k392haLSwy8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "D_only_layers_1_and_2 = pg.extract(D, layers = [1,2])\n",
    "qp(D_only_layers_1_and_2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "jewish-junction",
   "metadata": {},
   "source": [
    "Note that the Device created from this function is flattened"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "crucial-master",
   "metadata": {},
   "source": [
    "### Copying layers to a new layer\n",
    "\n",
    "Sometimes you want to copy a layer out of a Device AND remap that layer to a new layer in a single command.  You can do that with the `copy_layer()` function.  Let's try this out by taking the above geometry:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "developmental-deployment",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "qp(D)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "identified-orbit",
   "metadata": {},
   "source": [
    "...and let's copy the arc (yellow / layer 3) arc to a new layer (blue / layer 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "excellent-particle",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "D_copied = pg.copy_layer(D, layer = 3, new_layer = 1)\n",
    "qp(D_copied)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
